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Research Areas
  Positive Computing
  • Positive Computing is referred as design and development of technology to support well-being and human potential. Research in this area focuses on measuring and designing the impact of technologies on the psychological well-being of the people who use them. In order to design mobile systems for wellbeing effectively, researchers need to work together with the scientists from domains such as psychologists, sociologists, and neuroscientists in order to ensure evidence-based validation. In collaboration with the specialists, we proposed an intelligent large-scale data collection platform and develop key components based on guidelines for intelligent positive computing systems [Ad Hoc Networks'19]. A recent work in collaboration with other research teams, we proposed MindForecaster suggesting design implications for stress management by incorporating the properties of anticipation into current PI models [CHI'20].
  SDN Wi-Fi Management Framework
  • Due to advances in wireless technologies, we are live with plethora of WiFi access points (APs). Despite the advancements in WiFi technology over the years, users still experience poor performance and coverage. In this project, we present an academic SDN framework for providing easy WiFi configurability, which aims to provide users with the fast and reliable network service. To allow abstraction of easy and flexible configurability to legacy APs, we leverage SDN technologies that facilitate network management (e.g., channel allocation, power control, etc.) and policy enforcement (e.g., rate adaptation, flow prioritization, buffer management, etc.) in a centralized manner. This work includes OpenFlow WiFi testbed in public, extending programmability (i.e., channel allocation, power control, buffer management) of OpenFlow AP, and designing configuration specific language for OpenFlow APs.
  Big-data Processing Frameworks
  • Big-data processing frameworks like Hadoop and Spark, often used in multi-user environments, have struggled to achieve a balance between the full utilization of cluster resources and fairness between users. In particular, data locality becomes a concern, as enforcing fairness policies may cause poor placement of tasks in relation to the data on which they operate. To combat this, the schedulers in many frameworks use a heuristic called delay scheduling, which involves waiting for a short, constant interval for data-local task slots to become free if none are available; however, a fixed delay interval is inefficient, as the ideal time to delay varies depending on input data size, network conditions, and other factors. We propose an adaptive solution (Dynamic Delay Scheduling), which uses a simple feedback metric from finished tasks to adapt the delay scheduling interval for subsequent tasks at runtime. We present a dynamic delay implementation in Spark, and show that it outperforms a fixed delay in TPC-H benchmarks. Our preliminary experiments confirm our intuition that job latency in batch-processing scheduling can be improved using simple adaptive techniques with almost no extra state overhead.
  Indoor Localization and Energy Efficient Place Logging Flatform
  • Infrastructure-less Indoor Localization: Our goal was to realize indoor location aware application service in a time-critical scenario with a team of soldiers or first responders conducting emergency mission operations in a large building in which infrastructure-based localization is not feasible (e.g., due to management/installation costs, power outage, terrorist attacks). To achieve this, we design and implement a collaborative indoor positioning scheme (CLIPS) that requires no preexisting indoor infrastructure [PerCom13]. We assume that each user has a received signal strength map for the area in reference. This is used by the application to compare and select a set of feasible positions, when the device receives actual signal strength values at run time. Then, dead reckoning is performed to remove invalid candidate coordinates eventually leaving only the correct one which can be shared amongst the team.
  • PlaceWalker - Fine-grained place logging with Wi-Fi beacon signatures provides a useful tool for delivering various semantic location-aware services such as reminders and advertisements. Existing solutions however heavily rely on energy-hungry periodic Wi-Fi scanning for place detection in resource limited mobile devices. To cope with this, we design and implement PlaceWalker, a scheme that uses a low-power duty-cycled accelerometer in the background to continuously monitor user’s significant physical activity changes (e.g., walking to resting) as it provides a useful clue to the change of place [PMC14]. Unlike existing schemes, PlaceWalker triggers Wi-Fi scanning only when such an activity shift is detected and then determines a change of place by comparing Wi-Fi signatures.
  Content Distribution in People Networks
  • Recent advances of technology in consumer electronics have promoted a lifestyle where people live with convenience and ease by accessing any kind of information at their fingertips. These devices also allow people to generate/share a sheer amount of personal content such as photos, videos, and documents. However, personal content is now exploding and personal content sharing/management is considered to be a challenging task particularly when users need to deal with personal content scattered over multiple devices. To mitigate this problem, we aimed at enabling seamless access of personal content without specifying its location via content centric networking (CCN) over personal content. We proposed a platform called personal content networking (PCN) [WPC15] that uses a single persistent, hierarchical naming space for personal content, allows users to securely initialize their devices and establish trust with other users. This enables efficient content management over multiple devices (e.g., updates, removal, replication) and supports content centric access control via attribute-based encryption (ABE) for selective sharing where access control is not tied into hosts and yet fine-grained attribute based access control is permitted. We demonstrate its feasibility with prototype implementation on the basis of CCNx.
 Underwater/Drifting Sensor Networks
  • As part of our interest in mobile sensor platforms, our group has been studying underwater sensor networks where a swarm of mobile, unmanned low-cost sensor nodes monitors and reports underwater events and conditions. Given that the major challenges of underwater networking are the ocean current and the limited resources (bandwidth and energy), our group has been working on various underwater data harvesting protocols, namely medium access control protocols, multi-hop routing protocols, and location services.
  • For medium access control, we proposed the Delay-aware Opportunistic Transmission Scheduling (DOTS) algorithm that uses passively obtained local information (i.e., neighboring nodes’ propagation delay map and their expected transmission schedules) to increase the chances of concurrent transmissions while reducing the likelihood of collisions. However, DOTS’s temporal reuse ability is limited to the receiver side only. While each receiver supports multiple sessions from different neighboring senders, there is no support for a sender to open multiple sessions to the same destination [ICNP'10], [TMC'14]. To improve the overall throughput, we propose the Multi-session FAMA (M-FAMA) algorithm, which leverages passively-obtained local information (i.e., neighboring nodes’ propagation delay maps and expected transmission schedules) to enable simultaneous communications sessions while reducing the likelihood of collisions [INFOCOM'13].
  • For multi-hop routing, we proposed HydroCast, a hydraulic pressure based anycast routing protocol that exploits the measured pressure levels to route data to surface buoys [4-5]. In sparse underwater networks, the greedy stateless perimeter routing method, very popular in 2D networks, cannot be extended to void recovery in 3D networks. To cope with this challenge, we propose a Void Aware Pressure Routing (VAPR) protocol that uses sequence number, hop count, and depth information embedded in periodic beacons to set up next-hop direction and to build a directional trail to the closest sonobuoy. Using this trail, opportunistic directional forwarding can be efficiently performed even in the presence of voids [INFOCOM'10], [TMC'13].
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